We are in our new linux environment and create automake and autoconf used to generate configuration scripts for building more packages in your system.

We use Bubblewrap to install a progressive web app on android. Bubblewrap will create a signed Android APK from the progressive web app manifest and install it on your phone or upload it to Google play store.

We are in our new Linux environment and create BASH the Bourne Again SHell that we will use for our command-line environment and grep to find text using regular expressions.

In this video we will convert Pytorch model to Tensorflow using (Open Neural Network Exchange) ONNX. ONNX is a standard format supported by a community of partners such as Microsoft, Amazon and IBM. PyTorch is mainly maintained by Facebook and Tensorflow is built in collaboration with Google.

We use an easy method to retrain a pre-trained model for object classification. Transfer learning is an easy and quick method to retrain a model for good classification of objects.

In this video we are using fetch to do a file upload. File uploads could be hard if you haven’t done it before, fetch is a new api that can simplify the process.

We use Munin to monitor servers with different resources and critical operations. Munin will contact each server and ask for statistics and monitor if a service is running and have enough resources to work.

The next release of OpenJDK is number 15. I will title this release unsafe garbage as it focuses on garbage collection and removing usages of unsafe methods. We also look at string blocks and records.

We look into high availability using Heartbeat and DRBD. Heartbeat is a software to monitor and failover when a machine is unresponsive and DRBD can help you replicate data between machines making your setup highly available. This solution can help you doing maintenance work without downtime.

We will use the Github actions and create a progressive web app and test it using lighthouse ci. I will also go through improvements I’ve done from the report CI in lighthouse.

Using openfaas and minikube we will create a function as a service on prem. Function as a service is available for larger kubernetes systems and can be deployed in the cloud but being able to test locally can be benificial.

We look into scaling Kubernetes using a RabbitMQ queue or using horizontal autoscaling. There are guides for autoscaling using CPU, and I found a repository for RabbitMQ scaling. I will do the operations I’ve detailed in the git repository below.